To the extent of our knowledge, no other optimization algorithm is capable of handling mixed-variable, multi-objective problems in small-data settings. Thus, we have no direct comparisons between MixMOBO and other published algorithms. Therefore, we tested MixMOBO against a variant of NSGA-II [1]} with the ZDT4 and ZDT6 test functions with mixed variables. However, we found that using a GA required more than \(10^2\)  more function calls to find the Pareto front to a similar tolerance. For visualization purposes, we do not plot the GA results.
